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Dream2Real: Zero-Shot 3D Object Rearrangement with Vision-Language Models
We introduce Dream2Real, a robotics framework which integrates vision-language models (VLMs) trained on 2D data into a 3D object rearrangement pipeline.
SceneScore: Learning a Cost Function for Object Arrangement
Arranging objects correctly is a key capability for robots which unlocks a wide range of useful tasks.
DALL-E-Bot: Introducing Web-Scale Diffusion Models to Robotics
We introduce the first work to explore web-scale diffusion models for robotics.
My House, My Rules: Learning Tidying Preferences with Graph Neural Networks
Robots that arrange household objects should do so according to the user's preferences, which are inherently subjective and difficult to model.
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